R Notebook

beds_specialty <- read_csv("raw_data/beds_specialty.csv") %>%
  clean_names()

Rows: 30394 Columns: 20
── Column specification ──────────────────────────────────────────────────────────────────────────────────────────
Delimiter: ","
chr (10): Quarter, QuarterQF, HB, HBQF, Location, LocationQF, Specialty, SpecialtyQF, SpecialtyName, Specialty...
dbl  (5): AllStaffedBeds, TotalOccupiedBeds, AverageAvailableStaffedBeds, AverageOccupiedBeds, PercentageOccup...
lgl  (5): AllStaffedBedsQF, TotalOccupiedBedsQF, AverageAvailableStaffedBedsQF, AverageOccupiedBedsQF, Percent...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

map_beds <- beds_specialty %>%
  filter(location_qf == "d") %>% 
  mutate(year = year(yq(quarter)),
         quarter = str_sub(quarter, -2),
         winter_flag = if_else(quarter %in% c("Q1", "Q4"), "Winter", "Summer")) %>%
  select(year, winter_flag, hb, specialty_name, percentage_occupancy) %>% 
  group_by(winter_flag, year, hb) %>% 
  summarise(percentage_occupancy = mean(percentage_occupancy)) %>% 
  mutate(hb_name = case_when(
    hb == "S92000003" ~ "Scotland",
    hb == "S08000015" ~ "Ayrshire & Arran",
    hb == "S08000016" ~ "Borders",
    hb == "S08000017" ~ "Dumfries & Galloway",
    hb == "S08000019" ~ "Forth Valley",
    hb == "S08000020" ~ "Grampian",
    hb == "S08000022" ~ "Highland",
    hb == "S08000024" ~ "Lothian",
    hb == "S08000025" ~ "Orkney",
    hb == "S08000026" ~ "Shetland",
    hb == "S08000028" ~ "Western Isles",
    hb == "S08000029" ~ "Fife",
    hb == "S08000030" ~ "Tayside",
    hb == "S08000031" ~ "Greater Glasgow & Clyde",
    hb == "S08000032" ~"Lanarkshire",
    TRUE ~ as.character(NA))) %>% 
  filter(!is.na(hb_name)) %>% 
  rename(hb_code = hb)

`summarise()` has grouped output by 'winter_flag', 'year'. You can override using the `.groups` argument.

write_csv(map_beds, "clean_data/map_beds.csv")

simplified_shapes <- st_transform(rmapshaper::ms_simplify(st_read(
  "raw_data/nhs_hb_2019/nhs_hb_2019.shp")),"CRS:84") %>%
  clean_names()

Reading layer `nhs_hb_2019' from data source 
  `/Users/reutersvard/codeclan/de11_project/raw_data/nhs_hb_2019/nhs_hb_2019.shp' using driver `ESRI Shapefile'
Simple feature collection with 14 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 5512.998 ymin: 530250.8 xmax: 470332 ymax: 1220302
Projected CRS: OSGB 1936 / British National Grid

# st_write(simplified_shapes, "clean_data/hb_clean.shp") If it doesn't exist, create a clean shapes file
rm(beds_specialty, map_beds, simplified_shapes)

map_beds <- read_csv("clean_data/map_beds.csv")

Rows: 180 Columns: 5
── Column specification ──────────────────────────────────────────────────────────────────────────────────────────
Delimiter: ","
chr (3): winter_flag, hb_code, hb_name
dbl (2): year, percentage_occupancy

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

  
filtered_beds <- map_beds %>%
  filter(year == 2020,
         winter_flag == "Winter")

shapes <- st_read("clean_data/hb_clean.shp")

Reading layer `hb_clean' from data source `/Users/reutersvard/codeclan/de11_project/clean_data/hb_clean.shp' using driver `ESRI Shapefile'
Simple feature collection with 14 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -8.649439 ymin: 54.63336 xmax: -0.7251864 ymax: 60.86076
Geodetic CRS:  WGS 84

merged <- sp::merge(shapes, filtered_beds) %>% 
  select(hb_name, percentage_occupancy, geometry)

pal <- colorBin("BuPu", domain = merged$percentage_occupancy)

merged %>%
  leaflet() %>%
  addTiles() %>%
  addProviderTiles(providers$OpenStreetMap) %>%
  addPolygons(
    fillColor = ~ pal(percentage_occupancy),
    weight = 2,
    opacity = 1,
    color = "white",
    dashArray = "3",
    fillOpacity = 0.7,
    highlight = highlightOptions(
      weight = 5,
      color = "#666",
      dashArray = "",
      fillOpacity = 0.7,
      bringToFront = TRUE),
    label = paste0(merged$hb_name, ":", " ", round(merged$percentage_occupancy), "%"),
    labelOptions = labelOptions(
      style = list("font-weight" = "normal", padding = "3px 8px"),
      textsize = "15px",
      direction = "auto"),
    popup = paste0(merged$hb_name, ":", " ", round(merged$percentage_occupancy, digits = 2), "%")) %>%
  leaflet::addLegend("topleft", pal = pal, values = ~percentage_occupancy,
    title = "Bed Occupancy",
    opacity = 1)